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The value of electronic waste at present is estimated to increase rapidly year after year, and with rapid advances in electronics, shows no signs of slowing down. Storage devices such as SATA Hard Disks and Solid State Devices are electronic devices with high value recyclable raw materials which often goes unrecovered. Most of the e-waste currently generated, including HDDs, is either managed by the informal recycling sector, or is improperly landfilled with the municipal solid waste, primarily due to insufficient recovery infrastructure and labor shortage in the recycling industry. This emphasizes the importance of developing modern advanced recycling technologies such as robotic disassembly. Performing smooth robotic disassembly operations of precision electronics necessitates fast and accurate geometric 3D profiling to provide a quick and precise location of key components. Fringe Projection Profilometry (FPP), as a variation of the well-known structured light technology, provides both the high speed and high accuracy needed to accomplish this. However, Using FPP for disassembly of high-precision electronics such as hard disks can be especially challenging, given that the hard disk platter is almost completely reflective. Furthermore, the metallic nature of its various components make it difficult to render an accurate 3D reconstruction. To address this challenge, We have developed a single-shot approach to predict the 3D point cloud of these devices using a combination of computer graphics, fringe projection, and deep learning. We calibrate a physical FPP-based 3D shape measurement system and set up its digital twin using computer graphics. We capture HDD and SSD CAD models at various orientations to generate virtual training datasets consisting of fringe images and their point cloud reconstructions. This is used to train the U-NET which is then found efficient to predict the depth of the parts to a high accuracy with only a single shot fringe image. This proposed technology has the potential to serve as a valuable fast 3D vision tool for robotic re-manufacturing and is a stepping stone for building a completely automated assembly system.
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The Global Flow of Hard Disk Drives: Quantifying the Concept of Value Leakage in E‐waste Recovery Systems
Summary The remaining value within end‐of‐use/life hard disk drives (EoU/L HDDs) is often not optimally recovered. The improper collection and recovery of HDDs contribute not only to rising environmental and social concerns worldwide, but also to the transformation of the economy and a significant loss of value. Currently, the most preferred treatment option for used hard drives is to recover the metals with the highest recycling effectiveness, such as steel and aluminum, via a shredding‐based recycling process that results in both value and material leakages. The complexity of retrieving the remaining values within EoU/L HDDs demands a larger view of the global supply of HDDs available for recovery. The aim of this paper is to first identify the geographical patterns of transboundary global shipments of new and used HDDs between developing and developed regions, and then capture and quantify the value leakage by bringing several unique perspectives. Two analyses have been conducted. First, the loss of value due to the insufficient recovery of neodymium (Nd) at the global level is quantified. Second, the value leakage as a result of the delay on on‐time reuse of HDDs is captured. Furthermore, the central challenges toward proper recovery of HDDs, where consumer electronic industry can make significant contributions, have been identified. HDDs are well positioned to contribute important insights to the recovery of other electronic devices, so the findings from HDDs can be adopted for other types of electronics.
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- PAR ID:
- 10056665
- Publisher / Repository:
- Springer Science + Business Media
- Date Published:
- Journal Name:
- Journal of Industrial Ecology
- Volume:
- 23
- Issue:
- 3
- ISSN:
- 1088-1980
- Format(s):
- Medium: X Size: p. 560-573
- Size(s):
- p. 560-573
- Sponsoring Org:
- National Science Foundation
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